In December 2015 we ported 955K lines of QuantLib C++ code to asm.js. This positions us to provide unique services around hedge fund and Financial markets applications and more. This technology unchains a wealth of quantitative Functions.
Customers demand compelling financial markets tools solutions for Amazon Web Services and we're here to deliver.
While closed-source providers offer solutions, an Open Source Quant distribution enables optimization to run on Amazon Web Services C4 and GPU 2 instance types, and fleets of docker containers.
Today large and midmarket financial firms recognize how the future of quantitative finance is in the Cloud and have taken a hard and sharp turn in this direction. These firms recognize they need to move quickly. Bronze Drum's Carbon09 Quantitative Finance distributions optimized for AWS power this move to the cloud.
While the innovation of Open Source software development unleashed substantial innovation, data remains the lifeblood of financial firms. What is required to create a new ecosystem of microservices in the Cloud, each composed of single function services. While Fintech to-date largely focuses on the consumer side of services, financial firms seek answers to the question of how to leave incredibly valuable libraries of legacy code behind.
While in the Cloud Community substantial capital has been raised by firms that simply (well, we know it isn't actually easy) make it simpler to use open source software like Cassandra, Hadoop, Apache Spark such solutions solve the distribution, packaging and build challenge but leave others as an implementation detail. Such solutions are extremely valuable as they save firms enormous amounts of time.
Cloud Computing is an unfortunate term which hides the real-story of a Devonian scale extinction of firms. Software as we've known it is no more. Serverless Computing reduces the friction to a greater degree. Simply to wrangle with an Open Source project and get it to build and install takes hours and days and requires continuous effort. Developers of risk solutions, when they can break away from the enormous amount of compliance and change control documentation that grows daily, have little time left to wrangle with builds.
As financial services reduces costs so as to free working capital for investment, product innovation becomes even more critical, even as the constraint--developers--become mired in the code of yesterday. Rapid development in languages like Python improves matters considerably. Yet code is code. And much of the code is repeated across organizations, across projects, and it all must be debugged--or not. In financial services, bugs are costly when found in production. Knight Trading certainly learned the hard way that the old ways of building applications a line of code at a time can destroy a business in minutes.
Developers in financial services leverage Open Source libraries such as QuantLib, yet even so, considerable experience with the library is necessary to become productive. And while the library certainly is designed to avoid certain types of mistakes, in many cases the library requires substantial augmentation. The develop must write significant new code in many cases. On the whole, while object oriented programming and C++ and scripting languages are a substantial improvement, they don't actually do much to change the metaphor of developers moving grains of sand with chopticks as they build small castles. What's needed is a building block that is self-contained, and small enough that multiple projects can begin to use microservices composed on the functional units of composition. We've taken some simple examples from QuantLib and transcompiled these examples to ASM.js using the remarkable Mozilla project, Emscripten.
Public cloud significantly reduces the infrastructure and compute barrier to entry to financial markets. Further, the ability to write automated software to manage complex new compliance requirements remains a challenge for even the largest firms, some of which exited key markets such as derivatives and fixed income in 2015.[/cs_text][cs_text]SPReD
JP Morgan, Goldman Sachs, Morgan Stanley announced a multi-million dollar initiative to cut costs by aggregating, cleaning, and consuming their own Financial Markets Reference Data. Today these firms purchase such data from suppliers such as Bloomberg, Reuters, Six Financial, and others.[/cs_text][x_custom_headline level="h2" looks_like="h5" accent="false"]Ecosystem and Network Effects[/x_custom_headline][cs_text]
In New York City finance the community of quants is small and close knit. Rather than write libraries from scratch, firms today choose to build on Quantlib. While commercial third-party solutions exist and offer a great deal, QuantLib, and Open Source software is a particularly good fit for financial markets.
Stay up to date on our latest posts.